distribution shift

What are the Statistical Limits of Offline RL with Linear Function Approximation? ICLR 2021 What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? ICML 2021 Why did the distribution change? AISTATS 2021 WILDS: A Benchmark of in-the-Wild Distribution Shifts ICML 2021 An Unbiased Risk Estimator for Learning with Augmented Classes NeurIPS 2020 AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty ICLR 2020 A Unified View of Label Shift Estimation NeurIPS 2020 Bridging Causality and Learning: How Do They Benefit from Each Other? IJCAI 2020 Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? ICML 2020 Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets AAAI 2020 CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances NeurIPS 2020 Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision CVPR 2020 Estimating Generalization under Distribution Shifts via Domain-Invariant Representations ICML 2020 Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests NeurIPS 2020 Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data CVPR 2020 Hidden Risks of Machine Learning Applied to Healthcare: Unintended Feedback Loops Between Models and Future Data Causing Model Degradation MLHC 2020 Inferring Continuous Treatment Doses from Historical Data via Model-Based Entropy-Regularized Reinforcement Learning ACML 2020 Label-Noise Robust Domain Adaptation ICML 2020 Learning with Feature and Distribution Evolvable Streams ICML 2020 LTF: A Label Transformation Framework for Correcting Label Shift ICML 2020 Measuring Robustness to Natural Distribution Shifts in Image Classification NeurIPS 2020 Multidimensional Shape Constraints ICML 2020 On Numerosity of Deep Neural Networks NeurIPS 2020 On the "steerability" of generative adversarial networks ICLR 2020 On the Trade-off between Adversarial and Backdoor Robustness NeurIPS 2020